Many companies are investing in coaching services for professional drivers with the goal of teaching them how to reduce fuel usage, as well as other eco-driving skills. To succeed, a clear perception of the variations in fuel consumption that can be attributed to driving behavior is required.
Currently, vehicles operated by CGI client Scania Group, a leading global transport provider, are equipped with monitoring devices that generate both driver and vehicle data. This allows us to relate fuel consumption with data gathered using a CAN Bus (controller area network) and from other sources like weather.
To model the relation, we combined predictive analytics with Scania data on more than three million trips completed across seven European Union countries. In this paper, we explain the methods used and models built that allow for comparisons of the impact of ecodriving coaching for different fleets and countries.
We also discuss unexpected statistical relations encountered during the analysis. In addition, we propose an estimated effect of coaching (EEOC), which provides a realistic estimate of the fuel savings to be gained from eco-driving coaching.
